1. Field of the Invention
The present invention relates, in general, to an attitude correction apparatus for an Inertial Navigation System (INS) using a camera-type solar sensor and, more particularly, to a system for correcting errors occurring in an inertial navigation system, in which inertial sensors, such as a gyroscope and an accelerometer, are combined with each other and are adapted to calculate the attitude, velocity and position of an airplane, and to an apparatus for analyzing a sun-line of sight vector, generated by the camera-type solar sensor using an image of the moving sun and the output value of the inertial navigation system, thus correcting the attitude of an airplane and the errors of sensors.
2. Description of the Related Art
Generally, representative devices for measuring the motion status of an airplane include an Inertial Measurement Unit (IMU) for measuring angular velocity and acceleration, an Attitude Heading Reference System (AHRS) for measuring angular velocity and acceleration and calculating an attitude and an azimuth angle, and an Inertial Navigation System (INS) for measuring angular velocity and acceleration and calculating all of an attitude, velocity and position. Each of the above devices is composed of inertial sensors, such as a gyroscope for measuring angular velocity and an accelerometer for measuring acceleration.
Thanks to the rapid development of the electronics industry, the performance of various types of sensors used in airplanes has rapidly improved for a given cost thereof. Sensors having the same function have been developed toward small size, light weight and low cost. Owing to the improvement of the performance versus cost of various types of parts, various new development projects using the parts have been attempted. The development of an Unmanned Aerial Vehicle (UAV) is a representative example of such development projects. Generally, in a conventional UAV, expensive parts, which perform integrated functions and have high precision and high reliability, are installed. Therefore, the development of an UAV system has been restrictively conducted only by large-scale enterprises or large-scale laboratories. However, in the past 10 years, because of the rapid development of low-priced and small-sized sensors, systems having these sensors installed therein can be implemented by universities or even by individuals, and thus such systems have rapidly spread in the world.
Such a small-sized UAV tends to be similar to a conventional expensive UAV from the standpoint of at least control or elementary navigation. However, in the case of navigation equipment implemented using low-priced and small-sized sensors, the maximum precision that has been realized to date is insufficient to install the navigation equipment in the UAV and to stably perform a guidance and navigation function for a long period of time. Therefore, in the case of UAVs developed by several universities in nations that are advanced in the field of aeronautics, an expensive AHRS or INS is generally installed.
Meanwhile, as the number of small-scale enterprises that combine various kinds of low-priced sensors with each other to implement an IMU or AHRS and sell the IMU or AHRS has rapidly increased, and because the size of markets therefor has increased, competition is becoming intense. For companies that assemble commercial parts to construct systems without having fundamental technologies, the technical levels thereof have been gradually made uniform. For example, the IMU from Cloud Cap Technology weighs less than 20 grams and measures angular velocity and acceleration on three axes. The IMU uses RS232 communication and the Controller Area Network (CAN) protocol, operates at a rate of 200 Hz or above, and has a price of less than 2,000 dollars.
As another example, there is an automatic flight control system which develops from Crista IMU, and which has a maximum dimension of about 10 cm, weighs 210 grams, and has a price of 7,500 dollars. Enterprises that develop and produce such automatic flight control systems may include various companies other than Cloud Cap, for example, Crossbow, MicroPilot, etc. As described, such products have relatively low prices, and have functions that were impossible to implement at such low prices in the prior art.
FIG. 9 is a diagram showing the operating method of a typical Strapdown Inertial Navigation System (SINS). The basic operating principles of the method indicate a scheme for integrating angular velocity, as measured by a gyroscope, calculating the attitude angle of a payload, obtaining a coordinate transformation matrix on the basis of the attitude angle, transforming acceleration components in a local coordinate system, measured by an accelerometer, into components in an inertial coordinate system using the coordinate transformation matrix, and integrating the components in the inertial coordinate system, thus calculating velocity and position.
In FIG. 9, when it is assumed that, for example, an offset (bias) error exists in an angular velocity measured using a gyroscope, it can be seen that an offset error in an attitude angle gradually increases while an integral calculation process continues over time. The error in an attitude angle or direction cosine matrix is propagated in the form of an error in the calculation of velocity and position, thus deteriorating the overall reliability of the calculation results
Therefore, it is evident that perfect correction at the level of the parts of a gyroscope and an accelerometer is essentially required. However, an important problem is that there is a physical limitation in improvement of the precision of a system implemented using low-priced sensors. That is, since the magnitude of proof mass is limited, the amplification factor becomes inevitably large, and thus the system is more sensitive to noise.
Further, since a recent system has developed toward a system enabling mass production and supply for the purpose of low-cost supply, the correction of precision at the level of sensors is difficult, and variation in the characteristics of the sensors is sensitively affected by variation in the external environment. Even if correction at the level of the sensors is satisfactorily performed, errors in attitude, position and velocity inevitably accumulate when the system is continuously used for a long period of time, as in the case of long-distance navigation. That is, it can be seen that an INS using only an IMU has a tendency to generate divergent errors. The use of auxiliary sensors capable of performing mutual compensation is a method which has been proposed as a method of overcoming divergent errors and which is actively being developed.
An IMU is advantageous in that it generally has high-speed response characteristics and is not influenced by disturbance. However, the IMU has properties in that the output of the sensors of a gyroscope or accelerometer is accumulated, so that precise correction at the level of the sensors is essential, and the IMU is greatly influenced by the results of precise correction. However, when low-priced sensors are combined with other and used, there is a limitation in the improvement of the precision and accuracy of sensors in general, so that products using the sensors necessarily have errors which are divergent. For a method of overcoming divergent errors, research on a method of maximizing efficiency using both signals generated in the IMU, and signals measured by sensors having non-divergent error characteristics, such as a Global Positioning System (GPS), by utilizing auxiliary sensors, such as the GPS or a magnetometer, has recently been conducted. Such a technology is referred to as integrated navigation. Among technologies pertaining to integrated navigation, the most promising technology that has been actively developed is a system in which an INS and a GPS are combined with each other. The basic flowchart of this system is shown in FIG. 10.
A GPS is one of the sensors used to detect translation velocity and position in an inertial coordinate system. A GPS sensor can generally detect a current position of an airplane anywhere in the world with an error of the range of several tens of meters, and has a characteristic such that errors are not divergent, unlike the INS. The position estimated using signals output from a gyroscope and an accelerometer has errors increasing with the lapse of time. These errors are corrected using a position signal output from the GPS, and error characteristics used for correction are fed back both into the gyroscope and the accelerometer, and thus error correction is performed in real time. The GPS generally has an operating rate lower than that of the INS. Therefore, a GPS having high specification, among GPSs used for unmanned aerial vehicles, operates at a rate of about 10 Hz, and a GPS used for a general-purpose receiver generally operates at an operating rate of about 1 Hz. Therefore, in the case of an INS operating at a rate of about 200 Hz, a procedure for calculating attitude and position 200 times using the signals output from a gyroscope and an accelerometer, correcting the attitude and the position on the basis of position data if the position data is output from the GPS after one second has elapsed, and varying error characteristics, is continuously repeated, thus maximally utilizing the advantages of the INS, and minimizing the influence of divergent errors. Recently, since a GPS receiver gradually has light weight and low price, a low-priced INS used for small-sized unmanned aerial vehicles also has taken such a structure.
This structure has extended to a system in which auxiliary sensors, other than GPS, are combined with the INS. For example, a scheme of combining a magnetometer and an atmospheric sensor with the INS has been attempted. The magnetometer uses a method of estimating the attitude of an airplane using variation in a magnetic field vector on the basis of the fact that a detected magnetic vector varies according to attitude. The atmospheric sensor uses a method of correcting the INS using an atmospheric velocity, or velocity and altitude information output from an altimeter. As described above, all of these auxiliary sensors have error characteristics indicating non-divergent errors. Recently, the number of auxiliary sensors combined with the INS gradually increases, and thus there may occur the case where the INS, the GPS, the magnetometer, and the atmospheric sensor are used together for medium or greater scale unmanned aerial vehicles in cooperation with each other.
However, it is apparent that a method of improving error characteristics using such an integrated sensor is not a method of ultimately compensating for deficiency of the precision and accuracy of a low-priced INS. Such a fact influences the reliability of a system, and shows that different characteristics are exhibited according to the type of auxiliary sensors. For example, in the case of INS/GPS combination which is most actively used, the interruption of GPS signals may fatally influence the reliability of a system. It is well known that the reception state for GPS signals is not necessarily excellent even if there is a gradual improvement. The causes of a failure in reception state may include intentional or unintentional communication disturbance, such as jamming, inferiority of the arrangement of visible satellites, etc.
Therefore, when divergent error of a low-priced INS is intended to be corrected using the GPS, the error of the INS appears without being corrected if no GPS signal is received, and thus the control, guidance and navigation of a system dependent on the low-priced INS may cause fatal results. The magnetometer also has weakness in such external factors. That is, the error of the magnetometer increases around an object strongly influencing a magnetic field, such as a high voltage wire or a magnetic body, and resulting data obtained from the magnetometer is not reliable. The atmospheric sensor cannot easily obtain precise data under various conditions of wind, temperature, density, etc. That is, such sensors have defects indicating that they are weak in external environmental factors.
Therefore, in order to overcome the defects, a method of integrally using various sensors is used. In this case, the conclusion that auxiliary sensors for integrated navigation must be implemented to be insensitive to external environments can be reached.
FIG. 11 illustrates the properties of a typical integrated navigation system. A solid line indicates the case where a precise INS is used, and a dotted line indicates the case where a low-priced imprecise INS is used. ‘x’ denotes a position signal measured by a GPS. The two INSs receive a correction signal from the GPS, and use the correction signal. Although not presented herein, position errors did not diverge over time even though the correction of the error constants of the INSs is slightly erroneous when the GPS operates normally. The results presented herein are obtained by interrupting a GPS signal in some intervals and evaluating the effects thereof in the above-described case. Referring to the results shown in FIG. 11, it can be seen that, in the case of the precise INS, a linear trace is relatively excellently maintained, whereas, in the case of the imprecise INS, errors rapidly accumulate when the correction signal from the GPS disappears.
In the case of the INS implemented using low-priced imprecise sensors, it is necessary to perform correction using auxiliary sensors, but, in this case, the auxiliary sensors require characteristics such that divergent errors are prevented and such that insensitivity to the external environment is realized.
Further, research on the control of the attitude of an airplane using a visual sensor and on the use of the visual sensor for navigation has been variously conducted. Since a visual sensor is stably operated without being influenced by the external environment when weather conditions are good, the visual sensor may be the most reliable sensor if the limited operation range thereof is taken into consideration. However, an attitude indicator using the currently proposed visual sensor is problematic in that the processing speed thereof is not sufficiently fast to be used to control an airplane in the case of typical images.
Another problem, occurring when an image output from the visual sensor is used without change, resides in that, if a moving object, such as a vehicle, is included in objects on the earth when an attempt is made to use the objects on the earth, it is difficult to determine the effects of the motion of the object relative to the motion of an airplane. In order to solve the above problem, a method using features such as the horizon has been proposed and used, but this method is also problematic in that it is also sensitive to the environment.
Attempts to construct a navigation system using commercial inertial sensors and GPS sensors that have limited precision, but have excellent performance versus cost and are easily obtained in the navigation systems field, and to realize the automatic flight and navigation of small-sized unmanned aerial vehicles using the navigation system, are constantly being made all over the world. Further, companies related to avionics and having various sizes are making efforts to improve the efficiency of navigation systems that use integrated navigation. Small-scale venture enterprises and medium-scale companies arising therefrom are intensely competing with each other in every aspect of the combination of INS with GPS, which is strongly associated with the explosive increase in the market for small-sized unmanned aerial vehicles. Navigation equipment is the core of the automatic flight control system of both manned and unmanned aerial vehicles. It can be sufficiently predicted that, if stable and reliable navigation equipment is popularized, the demand for unmanned aerial vehicles using such equipment will rapidly increase. The market for low-cost navigation equipment will also increase for unrelated reasons.